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Image annotation by large-scale content-based image retrieval

10 years 5 months ago
Image annotation by large-scale content-based image retrieval
Image annotation has been an active research topic in recent years due to its potentially large impact on both image understanding and Web image search. In this paper, we target at solving the automatic image annotation problem in a novel search and mining framework. Given an uncaptioned image, first in the search stage, we perform content-based image retrieval (CBIR) facilitated by high-dimensional indexing to find a set of visually similar images from a large-scale image database. The database consists of images crawled from the World Wide Web with rich annotations, e.g. titles and surrounding text. Then in the mining stage, a search result clustering technique is utilized to find most representative keywords from the annotations of the retrieved image subset. These keywords, after salience ranking, are finally used to annotate the uncaptioned image. Based on search technologies, this framework does not impose an explicit training stage, but efficiently leverages large-scale and wel...
Xirong Li, Le Chen, Lei Zhang, Fuzong Lin, Wei-Yin
Added 14 Jun 2010
Updated 14 Jun 2010
Type Conference
Year 2006
Where MM
Authors Xirong Li, Le Chen, Lei Zhang, Fuzong Lin, Wei-Ying Ma
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